Job Description
Artificial Intelligence (AI) is looking for an experienced Head – Adaptive Learning AI Systems to take ownership of the AI in Education charter at a senior level. This is a role for someone who has already operated at scale and is comfortable setting direction rather than simply following one.
The successful candidate will bring approximately 12 years of progressively senior experience, holding M.Sc (Data Science), with a demonstrated track record across Statistical Modelling, Deep Learning, Data Preprocessing, Python, AI in Education. Beyond individual capability, this role expects the person to mentor junior team members and represent the function in cross-departmental discussions.
Reporting relationships will be defined based on the final scope agreed at offer stage, and the role is based out of Lucknow on a hybrid arrangement. Compensation is benchmarked at INR 28.1-61.5 LPA, reflecting the seniority and scope of the position.
Success in this role will be measured less by task completion and more by the quality of judgement applied to ambiguous, high-stakes situations within ai in education.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Interested candidates should be prepared to walk through relevant past work during the interview process.
The package is structured with a fixed component, performance bonus, and standard health coverage. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Compensation includes standard statutory benefits along with performance-linked variable pay. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
References may be requested closer to the offer stage rather than at the start of the process. Internal job postings are open to employees who've completed a minimum tenure in their current role.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
High performers in this role typically move into a broader ownership scope within 18-24 months. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.
The successful candidate will bring approximately 12 years of progressively senior experience, holding M.Sc (Data Science), with a demonstrated track record across Statistical Modelling, Deep Learning, Data Preprocessing, Python, AI in Education. Beyond individual capability, this role expects the person to mentor junior team members and represent the function in cross-departmental discussions.
Reporting relationships will be defined based on the final scope agreed at offer stage, and the role is based out of Lucknow on a hybrid arrangement. Compensation is benchmarked at INR 28.1-61.5 LPA, reflecting the seniority and scope of the position.
Success in this role will be measured less by task completion and more by the quality of judgement applied to ambiguous, high-stakes situations within ai in education.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Interested candidates should be prepared to walk through relevant past work during the interview process.
The package is structured with a fixed component, performance bonus, and standard health coverage. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth.
Compensation includes standard statutory benefits along with performance-linked variable pay. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
References may be requested closer to the offer stage rather than at the start of the process. Internal job postings are open to employees who've completed a minimum tenure in their current role.
Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
High performers in this role typically move into a broader ownership scope within 18-24 months. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding.